Machine learning and algebraic approaches towards complete matter spectra in 4d F-theory

Machine learning and algebraic approaches towards complete matter spectra in 4d F-theory

Abstract Motivated by engineering vector-like (Higgs) pairs in the spectrum of 4d F-theory compactifications, we combine machine learning and algebraic geometry techniques to analyze line bundle cohomologies on families of holomorphic curves. To quantify jumps of these cohomologies, we first generat...

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Bibliographic Details
Main Authors: Martin Bies, Mirjam Cvetič, Ron Donagi, Ling Lin, Muyang Liu, Fabian Ruehle
Format: Article
Language:English
Published: SpringerOpen 2021-01-01
Series:Journal of High Energy Physics
Subjects:
Differential and Algebraic Geometry
F-Theory
Flux compactifications
Field Theories in Higher Dimensions
Online Access:https://doi.org/10.1007/JHEP01(2021)196

Internet

https://doi.org/10.1007/JHEP01(2021)196

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